A New Method Based on Association Rules Mining and Geo-filter for Mining Spatial Association Knowledge

LIU Yaolin; XIE Peng; HE Qingsong; ZHAO Xiang; WEI Xiaojian; TAN Ronghui

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A New Method Based on Association Rules Mining and Geo-filter for Mining Spatial Association Knowledge

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摘要

Association rule mining methods, as a set of important data mining tools, could be used for mining spatial association rules of spatial data. However, applications of these methods are limited for mining results containing large number of redundant rules. In this paper, a new method named Geo-Filtered Association Rules Mining(GFARM) is proposed to effectively eliminate the redundant rules. An application of GFARM is performed as a case study in which association rules are discovered between building land distribution and potential driving factors in Wuhan, China from 1995 to 2015. Ten sets of regular sampling grids with different sizes are used for detecting the influence of multi-scales on GFARM. Results show that the proposed method can filter 50%–70% of redundant rules. GFARM is also successful in discovering spatial association pattern between building land distribution and driving factors.

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《中国地理科学：英文版》 |2017年第3期|389-401|共13页
作者
LIU Yaolin; XIE Peng; HE Qingsong; ZHAO Xiang; WEI Xiaojian; TAN Ronghui;
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作者单位

School of Resource and Environment Science;

Wuhan University;

Wuhan 430079;

China;

Key Laboratory of Geographic Informa-tion System;

Ministry of Education;

Wuhan University;

Wuhan 430079;

China;

Faculty of Geomaties;

East China Institute of Technol-ogy;

Nanehang 330013;

China;

The College of Management and Economics;

Tianjin University;

Tianjin 300072;

China;

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原文格式 PDF
正文语种 chi
中图分类测绘数据库与信息系统;
关键词
关联规则挖掘; 挖掘方法; 空间关联; 过滤; 地理; 知识; 数据挖掘工具; 冗余规则;

A New Method Based on Association Rules Mining and Geo-filter for Mining Spatial Association Knowledge

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